An extensive literature exists in the area of machine learning on the subject of prediction. A common approach is to infer prediction rules from the data of the form:                IF cond1 AND . . . condi . . . AND condm THEN predThese rules correspond to a set of conditions associated with a specific outcome. The challenge is to select conditions that are able to distinguish between whether an event occurs or not, but do not overfit available training data. A number of different techniques exist for this purpose, ranging from decision trees. However, current techniques are typically insufficient for discovering potentially predictive activity preceding acute events.        